Reconstructing persistent graph structures from noisy images

dc.creator	Chernov, Alexey	es
dc.creator	Kurlin, Vitaliy	es
dc.date.accessioned	2015-07-02T07:21:48Z
dc.date.available	2015-07-02T07:21:48Z
dc.date.issued	2013	es
dc.identifier.issn	1885-4508	es
dc.identifier.uri	http://hdl.handle.net/11441/26521
dc.description.abstract	Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools.	es
dc.format	application/pdf	es
dc.language.iso	eng	es
dc.publisher	Universidad de Sevilla	es
dc.relation.ispartof	Image-A : Applicable Mathematics in Image Engineering, 3 (5), 19-22	es
dc.rights	Atribución-NoComercial-SinDerivadas 4.0 España	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	es
dc.subject	Graph reconstruction	es
dc.subject	Noisy image	es
dc.subject	Point cloud data	es
dc.subject	Persistent topology	es
dc.title	Reconstructing persistent graph structures from noisy images	es
dc.type	info:eu-repo/semantics/article	es
dc.type.version	info:eu-repo/semantics/publishedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.relation.publisherversion	http://institucional.us.es/revistas/imagen_a/5/art_4.pdf	es
dc.identifier.idus	https://idus.us.es/xmlui/handle/11441/26521

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